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Reliable interpretability of biology-inspired deep neural networks
Deep neural networks display impressive performance but suffer from limited interpretability. Biology-inspired deep learning, where the architecture of the computational graph is based on biological knowledge, enables unique interpretability where real-world concepts are encoded in hidden nodes, whi...
Autores principales: | Esser-Skala, Wolfgang, Fortelny, Nikolaus |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10564878/ https://www.ncbi.nlm.nih.gov/pubmed/37816807 http://dx.doi.org/10.1038/s41540-023-00310-8 |
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